Abstract by Molly Barrott
Machine Learning for Alzheimer\'s Prediction
3M The goal of this research project is to use machine learning to identify locations on the human genome that can be used to predict whether a person will develop Alzheimer’s disease. We have a dataset of genetic information for people with and without Alzheimer’s disease that consists of millions of locations on the genome that may be different from person to person. These locations are referred to as SNPs and account for most of the variations between individuals. I am applying a variety of filtering and data processing techniques to extract different combinations of SNPs that are likely to be influential in preventing or contributing to Alzheimer’s disease. This information is then used to train a machine learning model to predict if a person will develop Alzheimer’s or not.